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Cloud Migration Engineer

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Onsite

Cloud Migration Engineer

Accenture Solutions Pvt Ltd

Cloud Migration Engineer

Skills

Google Cloud PlatformDockerDevOpsGrafanaSplunkAIAWSAnsiblePrometheusKubernetesITILServiceNowTerraformAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

14 September 2026

What they need


Project Role : Cloud Migration Engineer

Project Role Description : Provides assessment of existing solutions and infrastructure to migrate to the cloud. Plan, deliver, and implement application and data migration with scalable, high-performance solutions using private and public cloud technologies driving next-generation business outcomes.

Must have skills : Cloud Strategy and Assessment

Good to have skills : NA
Minimum 12 year(s) of experience is required

Educational Qualification : 15 years full time education

ROLE OVERVIEW
15+ Years of experience
Associate Directory level - advisor leading enterprise IT infrastructure engagements spanning Cloud, AIOps, Generative AI, and Agentic AI from business case through architecture and client advisory. Client-facing at CxO level with active pre-sales involvement.
Key responsibilities

  • Develop business cases, TCO/ROI models, and FinOps strategies for cloud, AIOps, and AI transformation programmes.

  • Lead infrastructure maturity, cloud readiness, GenAI readiness, and Agentic AI assessments with gap analysis and roadmaps.

  • Architect cloud solutions (AWS, Azure, GCP) including landing zones, multi-cloud governance, and migration planning.

  • Design AIOps frameworks: observability, event correlation, auto-remediation, CMDB enrichment, and ITSM integration.

  • Advise on Generative AI adoption: RAG pipelines, vector databases, LLM fine-tuning, prompt engineering, and AI-ready infrastructure (GPU, InfiniBand, MLOps).

  • Design Agentic AI architectures: multi-agent orchestration, tool-use frameworks, autonomous workflows integrated with ITSM/ITOM.

  • Produce architecture deliverables: HLD, LLD, reference architectures, solution blueprints, and ADRs.

  • Design enterprise networks: SD-WAN, MPLS, SASE, ZTNA, NSX-T, and zero-trust security frameworks.

  • Serve as primary client-facing technical authority manage CxO relationships and steering committee representation.

  • Lead pre-sales: RFP/RFI responses, technical discovery, PoC proposals, solution demos, and bid governance.

  • Partner with sales teams on opportunity qualification (MEDDIC), SOW development, and commercial proposals.

  • Mentor consultants, contribute to practice development and repeatable pre-sales asset creation.

    TECHNICAL SKILLS

    Generative AI Azure OpenAI, AWS Bedrock, Vertex AI, GPT-4/Claude, RAG, vector DBs (Pinecone, pgvector), prompt engineering, LLM fine-tuning
    Agentic AI AutoGen, CrewAI, LangGraph, LangChain, LlamaIndex, MCP, tool-use frameworks, multi-agent orchestration, autonomous workflows
    AI Infra NVIDIA H100/A100, InfiniBand/RoCE, MLflow, Kubeflow, SageMaker, vLLM, Triton, AI observability, MLOps platforms
    Cloud AWS (EKS, VPC, Direct Connect), Azure (Landing Zones, AKS, ExpressRoute), GCP, multi-cloud governance, FinOps, CAF
    AIOps Dynatrace, Splunk ITSI, ServiceNow ITOM, Moogsoft, BigPanda, Prometheus, Grafana, OpenTelemetry, CMDB
    Network SD-WAN (Cisco/VMware/Fortinet), MPLS, BGP, SASE, ZTNA, NSX-T, Cisco ACI, Infoblox, SDP
    Compute VMware vSphere/vSAN/NSX, Nutanix HCI, Kubernetes, OpenShift, Terraform, Ansible, GitOps, Docker
    Security Zero Trust, ISO 27001, SOC 2, NIST CSF, IAM/PAM, EU AI Act, AI governance, SIEM, micro-segmentation
    Frameworks TOGAF, AWS Well-Architected, Azure CAF, ITIL 4, COBIT, SAFe, DevSecOps, Zachman

    TECHNICAL SKILLS
    Domain Technologies Skills
    Generative AI Azure OpenAI, AWS Bedrock, Vertex AI, GPT-4/Claude, RAG, vector DBs (Pinecone, pgvector), prompt engineering, LLM fine-tuning
    Agentic AI AutoGen, CrewAI, LangGraph, LangChain, LlamaIndex, MCP, tool-use frameworks, multi-agent orchestration, autonomous workflows
    AI Infra NVIDIA H100/A100, InfiniBand/RoCE, MLflow, Kubeflow, SageMaker, vLLM, Triton, AI observability, MLOps platforms
    Cloud AWS (EKS, VPC, Direct Connect), Azure (Landing Zones, AKS, ExpressRoute), GCP, multi-cloud governance, FinOps, CAF
    AIOps Dynatrace, Splunk ITSI, ServiceNow ITOM, Moogsoft, BigPanda, Prometheus, Grafana, OpenTelemetry, CMDB
    Network SD-WAN (Cisco/VMware/Fortinet), MPLS, BGP, SASE, ZTNA, NSX-T, Cisco ACI, Infoblox, SDP
    Compute VMware vSphere/vSAN/NSX, Nutanix HCI, Kubernetes, OpenShift, Terraform, Ansible, GitOps, Docker
    Security Zero Trust, ISO 27001, SOC 2, NIST CSF, IAM/PAM, EU AI Act, AI governance, SIEM, micro-segmentation
    Frameworks TOGAF, AWS Well-Architected, Azure CAF, ITIL 4, COBIT, SAFe, DevSecOps, Zachman
    REQUIRED QUALIFICATIONS

  • 15+ years IT infrastructure 5+ years consulting / advisory.

  • Proven cloud AIOps transformation programme delivery.

  • Business case development and executive stakeholder engagement.

  • Architecture deliverable ownership: HLD, LLD, ADRs, blueprints.

  • Strong client-facing, pre-sales, and bid management experience.

  • TOGAF, ITIL 4, or equivalent framework proficiency.
    PREFERRED QUALIFICATIONS

  • AWS / Azure / GCP Professional certification CCIE/CCDE.

  • Hands-on GenAI platforms: Azure OpenAI, Bedrock, Vertex AI.

  • Agentic AI frameworks: LangChain, AutoGen, CrewAI, LangGraph.

  • RAG pipeline design, vector DB implementation, LLM fine-tuning.

  • Regulated industry experience: FSI, healthcare, government.

  • Big 4 or boutique consulting background. MBA / MSc advantageous.
    KEY ATTRIBUTES

  • Executive presence confident at board, steering committee, and design authority level.

  • Commercial acumen translates complexity into business value drives pre-sales win rates.

  • Structured communicator boardroom decks, technical docs, winning bids.

  • Intellectually curious Generative AI, Agentic AI, cloud-native, platform engineering.

    CONSULTING SERVICE LINES

    Advisory- Cloud AI strategy
    AIOps operating model
    GenAI use-case advisory
    Agentic AI model design
    Vendor selection
    Business case FinOps

    Assessment

    Infra maturity review
    Cloud readiness
    GenAI/AI readiness
    Agentic AI maturity
    AIOps readiness
    DR/BC gap analysis

    Design Arch

    Cloud landing zones
    AI-ready infra design
    Agentic AI platform
    RAG vector DB design
    HLD / LLD / ADRs
    AIOps observabilityDD

    15 years of continue educations is required

    Qualification15 years full time education

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